Qualification:
PhD in Computer Engineering
MTech Computer Engineering, Govt. College of Engineering Amaravati, 2013
Experience:
Teaching 14 years
Research Interest/Area:
Artificial Intelligence, Knowledge Graph, Machine Learning, Deep Learning
Recent Teachings: (last three years teaching specified):
A.Y. 2023-24
Semester I: Artificial Intelligence (UG), Artificial Intelligence (PG)
Semester II: Introduction to Artificial Intelligence (UG)
A.Y. 2022-23
Semester I: Artificial Intelligence (UG), Artificial Intelligence (PG)
Semester II: Introduction to Artificial Intelligence (UG), Introduction to Artificial
Intelligence (PG-Mechatronics)
A.Y. 2021-22
Semester I: Artificial Intelligence (UG), Artificial Intelligence (PG)
Semester II: Data Analytics (PG), Introduction to Artificial Intelligence (UG),
Current Advises:
-
Programme
Name
Roll No
Joining Date
Title
MTech
Hutesh Vidhate
712222016
AY 2022-23
Knowledge graph embedding using CNN and BIRT
MTech
Dipak Jadhav
712299004
AY 2022-23
Graph convolution network for knowledge graph embedding
MTech
Akhilesh Chaudhari
122122003
AY 2021-22
Attention Mechanism in Knowledge Graph
MTech
Garima Mishra
122122008
AY 2021-22
Negative Sampling in Knowledge Graph
MTech
Omkar Shinde
122042013
AY 2020-21
Knowledge graph creation, embedding and completion of cyber-security knowledge graphs
MTech
Fawaz Wangde
122042021
AY 2020-21
Convolutional networks for
learning interaction knowledge graph embedding
MTech
Swapnil Mahure
122099008
AY 2020-21
Missing link prediction in
Art knowledge graph using representation learning
MTech
Akanksha Akulwar
121922001
AY 2019-20
Fake News Detection using Machine Learning Techniques
MTech
Navin Gopal
121942021
AY 2019-20
Movie recommendation using knowledge graph
Awards & Recognition:
Best paper award in International Conference on Recent Advanced in Industry 4.0 Technologies, NIT Puducherry, 2022, Manuscript Title: Convolutional Neural Network for Knowledge Graph Completion
Publication:
Anish Khobragade, Sanket Patil, Harsha Rathi, Shashikant Ghumbre, “Missing relation prediction in knowledge graph using local and neighbour aware entity embedding,” Journal of Discrete Mathematical Sciences & Cryptography, vol. 27, no. 4, pp. 1173–1184, 2024.
Anish Khobragade, Shashikant Ghumbre, and Vinod Pachghare, “Enhancing missing facts inference in knowledge graph using triplet subgraph attention embeddings,” Applied intelligence, vol. 54, no. 2, pp. 1497–1510, 2024.
Anish Khobragade, Shashikant Ghumbre, and Vinod Pachghare, “Infer the missing facts of D3FEND using knowledge graph representation learning,” International journal of Web information systems, vol. 19, no. 3/4, pp. 139–156, 2023.
Anish Khobragade and S. U. Ghumbre, “Study and analysis of various link predictions in knowledge graph: A challenging overview,” Intelligent decision technologies, vol. 16, no. 4, pp. 653–663, 2022.
Anish Khobragade, R. Mahajan, H. Langi, Rohit Mundhe, and Shashikant Ghumbre, “Effective negative triplet sampling for knowledge graph embedding,” Journal of information & optimization sciences, vol. 43, no. 8, pp. 2075–2087, 2022.
Anish Khobragade, Prashant Chatur, Deepak Asudani, “Effectiveness Evaluation of Regression Models for Predictive Data Mining” International Journal of Management, IT and Engineering, vol. 3, no. 3, pp. 465–483, Jan. 2013.
Anish Khobragade, Prashant Chatur, Deepak Asudani, “Mining Frequent Item sets with Diverse Association Rule Mining: A Survey”, International Journal of Management, IT and Engineering, vol. 3, no. 3, pp. 349–352, Jan. 2013.
Conference:
Anish Khobragade, Shashikant Ghumbre, and Fawaz Wangde. “Convolutional neural network for knowledge graph completion,” In AIP Conference Proceedings, vol. 2917, no. 1, 2023.
Anish Khobragade, Shashikant Ghumbre, and Vinod Pachghare. “Balance Relation-Aware Attention Embedding Model for Knowledge Graph Completion,” 2023 IEEE Pune Section International Conference (PuneCon), Pune, India, 2023, pp. 1-5.
Akhilesh Chaudhari, Anish Khobragade, Shashikant Ghumbre, “Analysis of Knowledge Graph Embedding Using Graph Attention Mechanism,” 2023 7th International Conference on Computing, Communication, Control and Automation (ICCUBEA), Pune, India, 2023, pp. 1-5.
Garima Mishra, Anish R Khobragade, Shashikant Ghumbre, “Analysis of Negative Sampling Methods for Knowledge Graph Embedding,” 2023 7th International Conference on Computing, Communication, Control and Automation (ICCUBEA), Pune, India, 2023, pp. 1-5.
Pooja V Agrawal, Deepak D Kshirsagar, Anish R Khobragade, “Symmetric uncertainty-based feature selection method in android malware detection,” Recent Advances in Material, Manufacturing, and Machine Learning, 2023, pp. 934-941.
Omkar Shinde, Anish Khobragade, Pooja Agrawal, “Static malware detection of Ember windows-PE API call using machine learning,” AIP Conference Proceedings, vol. 2724, no. 1, 2023
Omkar Shinde, Anish Khobragade, “Knowledge Graph creation on Windows malwares and completion using knowledge graph embedding,” 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 1980-1984.
Anish Khobragade, Ganesh Landge, Jayant Kalani, Akash Patil, “Tracing rumor source in large scale social network using onion model,” 2019 5th International Conference on Computing, Communication, Control and Automation (ICCUBEA), Pune, India, 2019, pp. 1-6.
